/*
* Copyright (C) 2010-2018 Arm Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/* ----------------------------------------------------------------------
* Project: CMSIS NN Library
* Title: arm_fully_connected_q15_opt.c
* Description: Q15 opt fully-connected layer function
*
* $Date: 17. January 2018
* $Revision: V.1.0.0
*
* Target Processor: Cortex-M cores
*
* -------------------------------------------------------------------- */
#include "arm_math.h"
#include "arm_nnfunctions.h"
/**
* @ingroup groupNN
*/
/**
* @addtogroup FC
* @{
*/
/**
* @brief Q15 opt fully-connected layer function
* @param[in] pV pointer to input vector
* @param[in] pM pointer to matrix weights
* @param[in] dim_vec length of the vector
* @param[in] num_of_rows number of rows in weight matrix
* @param[in] bias_shift amount of left-shift for bias
* @param[in] out_shift amount of right-shift for output
* @param[in] bias pointer to bias
* @param[in,out] pOut pointer to output vector
* @param[in,out] vec_buffer pointer to buffer space for input
* @return The function returns <code>ARM_MATH_SUCCESS</code>
*
*
* @details
*
* <b>Buffer size:</b>
*
* vec_buffer size: 0
*
* Here we use only one pointer to read 4 rows in the weight
* matrix. So if the original matrix looks like this:
*
* | a11 | a12 | a13 |
*
* | a21 | a22 | a23 |
*
* | a31 | a32 | a33 |
*
* | a41 | a42 | a43 |
*
* | a51 | a52 | a53 |
*
* | a61 | a62 | a63 |
*
* We operates on multiple-of-4 rows, so the first four rows becomes
*
* | a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
*
* | a13 | a23 | a33 | a43 |
*
* Remaining rows are kept the same original order.
*
* So the stored weight matrix looks like this:
*
*
* | a11 | a12 | a21 | a22 | a31 | a32 | a41 | a42 |
*
* | a13 | a23 | a33 | a43 | a51 | a52 | a53 | a61 |
*
* | a62 | a63 |
*/
arm_status
arm_fully_connected_q15_opt(const q15_t * pV,
const q15_t * pM,
const uint16_t dim_vec,
const uint16_t num_of_rows,
const uint16_t bias_shift,
const uint16_t out_shift,
const q15_t * bias,
q15_t * pOut,
q15_t * vec_buffer)
{
#if defined (ARM_MATH_DSP)
/* Run the following code for Cortex-M4 and Cortex-M7 */
const q15_t *pB = pM;
q15_t *pO = pOut;
const q15_t *pBias = bias;
const q15_t *pA = pV;
uint16_t rowCnt = num_of_rows >> 2;
while (rowCnt)
{
q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
q31_t sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
q31_t sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
q31_t sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
uint16_t colCnt = dim_vec >> 1;
pA = pV;
#ifdef USE_INTRINSIC
while (colCnt)
{
q31_t inM11, inM12, inM13, inM14;
q31_t inV;
inV = *__SIMD32(pA)++;
inM11 = *__SIMD32(pB)++;
sum = __SMLAD(inV, inM11, sum);
inM12 = *__SIMD32(pB)++;
sum2 = __SMLAD(inV, inM12, sum2);
inM13 = *__SIMD32(pB)++;
sum3 = __SMLAD(inV, inM13, sum3);
inM14 = *__SIMD32(pB)++;
sum4 = __SMLAD(inV, inM14, sum4);
colCnt--;
}
#else
/*
* register needed:
* loop counter: colCnt
* accumulators: sum, sum2, sum3, sum4
* pointers: pB, pA
* weight data: inM11, inM12, inM13, inM14
* activation data: inV
*/
asm volatile ("COL_LOOP_%=:\n"
"ldr.w r4, [%[pA]], #4\n"
"ldr.w r0, [%[pB]], #16\n"
"smlad %[sum], r4, r0, %[sum]\n"
"ldr.w r1, [%[pB] , #-12]\n"
"smlad %[sum2], r4, r1, %[sum2]\n"
"ldr.w r2, [%[pB] , #-8]\n"
"smlad %[sum3], r4, r2, %[sum3]\n"
"ldr.w r3, [%[pB] , #-4]\n"
"smlad %[sum4], r4, r3, %[sum4]\n"
"subs %[colCnt], #1\n"
"bne COL_LOOP_%=\n":[sum] "+r"(sum),
[sum2] "+r"(sum2),[sum3] "+r"(sum3),
[sum4] "+r"(sum4),[pB] "+r"(pB),[pA] "+r"(pA):[colCnt] "r"(colCnt):"r0", "r1", "r2", "r3", "r4");
#endif /* USE_INTRINSIC */
colCnt = dim_vec & 0x1;
while (colCnt)
{
q15_t inV = *pA++;
q15_t inM = *pB++;
q15_t inM2 = *pB++;
q15_t inM3 = *pB++;
q15_t inM4 = *pB++;
sum += inV * inM;
sum2 += inV * inM2;
sum3 += inV * inM3;
sum4 += inV * inM4;
colCnt--;
} /* while over colCnt */
*pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
*pO++ = (q15_t) (__SSAT((sum2 >> out_shift), 16));
*pO++ = (q15_t) (__SSAT((sum3 >> out_shift), 16));
*pO++ = (q15_t) (__SSAT((sum4 >> out_shift), 16));
/* adjust the pointers and counters */
rowCnt--;
}
/* left-over part of the rows */
rowCnt = num_of_rows & 0x3;
while (rowCnt)
{
q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
uint16_t colCnt = dim_vec >> 2;
pA = pV;
while (colCnt)
{
q31_t inV1, inV2, inM1, inM2;
inM1 = *__SIMD32(pB)++;
inV1 = *__SIMD32(pA)++;
sum = __SMLAD(inV1, inM1, sum);
inM2 = *__SIMD32(pB)++;
inV2 = *__SIMD32(pA)++;
sum = __SMLAD(inV2, inM2, sum);
colCnt--;
}
/* left-over of the vector */
colCnt = dim_vec & 0x3;
while (colCnt)
{
q15_t inV = *pA++;
q15_t inM = *pB++;
sum += inV * inM;
colCnt--;
}
*pO++ = (q15_t) (__SSAT((sum >> out_shift), 16));
rowCnt--;
}
#else
/* Run the following code as reference implementation for Cortex-M0 and Cortex-M3 */
uint16_t rowCnt = num_of_rows >> 2;
const q15_t *pB = pM;
const q15_t *pA;
q15_t *pO = pOut;
const q15_t *pBias = bias;
while (rowCnt)
{
q31_t sum = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
q31_t sum2 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
q31_t sum3 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
q31_t sum4 = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
uint16_t colCnt = dim_vec >> 1;
pA = pV;
while (colCnt)
{
q15_t inA1 = *pA++;
q15_t inA2 = *pA++;
q15_t inB1 = *pB++;
q15_t inB2 = *pB++;
sum += inA1 * inB1 + inA2 * inB2;
inB1 = *pB++;
inB2 = *pB++;
sum2 += inA1 * inB1 + inA2 * inB2;
inB1 = *pB++;
inB2 = *pB++;
sum3 += inA1 * inB1 + inA2 * inB2;
inB1 = *pB++;
inB2 = *pB++;
sum4 += inA1 * inB1 + inA2 * inB2;
colCnt--;
}
colCnt = dim_vec & 0x1;
while (colCnt)
{
q15_t inA = *pA++;
q15_t inB = *pB++;
sum += inA * inB;
inB = *pB++;
sum2 += inA * inB;
inB = *pB++;
sum3 += inA * inB;
inB = *pB++;
sum4 += inA * inB;
colCnt--;
}
*pO++ = (q15_t) __SSAT((sum >> out_shift), 16);
*pO++ = (q15_t) __SSAT((sum2 >> out_shift), 16);
*pO++ = (q15_t) __SSAT((sum3 >> out_shift), 16);
*pO++ = (q15_t) __SSAT((sum4 >> out_shift), 16);
rowCnt--;
}
rowCnt = num_of_rows & 0x3;
while (rowCnt)
{
int ip_out = ((q31_t)(*pBias++) << bias_shift) + NN_ROUND(out_shift);
int j;
pA = pV;
for (j = 0; j < dim_vec; j++)
{
q15_t inA = *pA++;
q15_t inB = *pB++;
ip_out += inA * inB;
}
*pO++ = (q15_t) __SSAT((ip_out >> out_shift), 16);
rowCnt--;
}
#endif /* ARM_MATH_DSP */
/* Return to ARM_MATH_SUCCESS */
return (ARM_MATH_SUCCESS);
}
/**
* @} end of FC group
*/
